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Background: Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up., Methods: Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4-14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5-<25·0 kg/m(2)., Findings: All-cause mortality was minimal at 20·0-25·0 kg/m(2) (HR 1·00, 95% CI 0·98-1·02 for BMI 20·0-<22·5 kg/m(2); 1·00, 0·99-1·01 for BMI 22·5-<25·0 kg/m(2)), and increased significantly both just below this range (1·13, 1·09-1·17 for BMI 18·5-<20·0 kg/m(2); 1·51, 1·43-1·59 for BMI 15·0-<18·5) and throughout the overweight range (1·07, 1·07-1·08 for BMI 25·0-<27·5 kg/m(2); 1·20, 1·18-1·22 for BMI 27·5-<30·0 kg/m(2)). The HR for obesity grade 1 (BMI 30·0-<35·0 kg/m(2)) was 1·45, 95% CI 1·41-1·48; the HR for obesity grade 2 (35·0-<40·0 kg/m(2)) was 1·94, 1·87-2·01; and the HR for obesity grade 3 (40·0-<60·0 kg/m(2)) was 2·76, 2·60-2·92. For BMI over 25·0 kg/m(2), mortality increased approximately log-linearly with BMI; the HR per 5 kg/m(2) units higher BMI was 1·39 (1·34-1·43) in Europe, 1·29 (1·26-1·32) in North America, 1·39 (1·34-1·44) in east Asia, and 1·31 (1·27-1·35) in Australia and New Zealand. This HR per 5 kg/m(2) units higher BMI (for BMI over 25 kg/m(2)) was greater in younger than older people (1·52, 95% CI 1·47-1·56, for BMI measured at 35-49 years vs 1·21, 1·17-1·25, for BMI measured at 70-89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46-1·56, vs 1·30, 1·26-1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI., Interpretation: The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations., Funding: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health., (Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC-BY license. Published by Elsevier Ltd.. All rights reserved.)

Background: Internationally there is limited empirical evidence on the impact of overweight and obesity on health service use and costs. We estimate the burden of hospitalisation-admissions, days and costs-associated with above-normal BMI., Methods: Population-based prospective cohort study involving 224,254 adults aged ≥45y in Australia (45 and Up Study). Baseline questionnaire data (2006-2009) were linked to hospitalisation and death records (median follow-up 3.42y) and hospital cost data. The relationships between BMI and hospital admissions and days were modelled using zero-inflated negative binomial regression; generalised gamma models were used to model costs. Analyses were stratified by sex and age (45-64, 65-79, ≥80y), and adjusted for age, area of residence, education, income, smoking, alcohol-intake and private health insurance status. Population attributable fractions were also calculated., Results: There were 459,346 admissions (0.55/person-year) and 1,483,523 hospital days (1.76/person-year) during follow-up. For ages 45-64y and 65-79y, rates of admissions, days and costs increased progressively with increments of above-normal BMI. Compared to BMI 22.5-<25kg/m2, rates of admissions and days were 1.64-2.54 times higher for BMI 40-50kg/m2; costs were 1.14-1.24 times higher for BMI 27.5-<30kg/m2, rising to 1.77-2.15 times for BMI 40-50kg/m2. The BMI-hospitalisation relationship was less clear for ≥80y. We estimated that among Australians 45-79y, around 1 in every 8 admissions are attributable to overweight and obesity (2% to overweight, 11% to obesity), as are 1 in every 6 days in hospital (2%, 16%) and 1 in every 6 dollars spent on hospitalisation (3%, 14%)., Conclusions: The dose-response relationship between BMI and hospital use and costs in mid-age and older Australians in the above-normal BMI range suggests even small downward shifts in BMI among these people could result in considerable reductions in their annual health care costs; whether this would result in long-term savings to the health care system is not known from this study.

Aims: We aimed to (1) assess the association between lipoprotein(a) [Lp(a)] concentration and incident type-2 diabetes in the Bruneck study, a prospective population-based study, and (2) combine findings with evidence from published studies in a literature-based meta-analysis. Methods: We used Cox proportional hazards models to calculate hazard ratios (HR) for incident type-2 diabetes over 20 years of follow-up in 815 participants of the Bruneck study according to their long-term average Lp(a) concentration. For the meta-analysis, we searched Medline, Embase and Web of Science for relevant prospective cohort studies published up to October 2016. Results: In the Bruneck study, there was a 12% higher risk of type-2 diabetes for a one standard deviation lower concentration of log Lp(a) (HR = 1.12 [95% CI 0.95-1.32]; P = 0.171), after adjustment for age, sex, alcohol consumption, body mass index, smoking status, socioeconomic status, physical activity, systolic blood pressure, HDL cholesterol, log high-sensitivity C-reactive protein and waist-hip ratio. In a meta-analysis involving four prospective cohorts with a total of 74,575 participants and 4514 incident events, the risk of type-2 diabetes was higher in the lowest two quintiles of Lp(a) concentrations (weighted mean Lp(a) = 3.3 and 7.0 mg/dL, respectively) compared to the highest quintile (62.9 mg/dL), with the highest risk of type-2 diabetes seen in quintile 1 (HR = 1.28 [1.14-1.43]; P < 0.001). Conclusions: The current available evidence from prospective studies suggests that there is an inverse association between Lp(a) concentration and risk of type-2 diabetes, with a higher risk of type-2 diabetes at low Lp(a) concentrations (approximately <7 mg/dL). [ABSTRACT FROM AUTHOR]

Objective: Antidepressant use is widespread. While weight gain is a commonly reported side-effect of antidepressant use and has the potential to affect population health, there is little large-scale population-based evidence on the issue, particularly for long-term use (⩾12 months). The aim of this study is to investigate the association between antidepressant use and weight change, including whether this relationship varies according to antidepressant class, recency of use, duration of use and dose. Methods: Annual percentage weight change was calculated from self-reported weight at two time-points from 20,751 participants aged ⩾45 years from the 45 and Up Study – a population-based cohort study from New South Wales, Australia. Antidepressant use, ascertained from linked pharmaceutical data, from 19 months before baseline until end of follow-up (mean = 3.3 years of follow-up), was categorised as current, past-only, non-persistent or non-use. The association between antidepressant use and weight change was modelled using linear and multinomial logistic regressions and according to antidepressant class, recency, duration and dose. Results: Antidepressants were dispensed to 23% of participants (n = 4748) during the study period. Current antidepressant users were significantly more likely to gain >3% of their body weight annually than non-users (adjusted relative risk ratio = 1.19; 95% confidence interval: [1.03, 1.38]); the risk increased with increasing dose among current users (p[trend] = 0.003). Risk of weight gain did not vary significantly according to antidepressant class, recency or duration of use; however, statistical power was limited. No significant associations were found between antidepressant use and weight loss. Conclusion: Current antidepressant use was associated with modest but statistically significant annual gains in weight, with similar effects observed across the different classes of antidepressants used. [ABSTRACT FROM AUTHOR]